There is a newer version of this record available.

Dataset Open Access

A Twitter Dataset of 100+ million tweets related to COVID-19

Banda, Juan M.; Tekumalla, Ramya; Wang, Guanyu; Yu, Jingyuan; Liu, Tuo; Ding, Yuning; Chowell, Gerardo


JSON-LD (schema.org) Export

{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p><strong>Due to the relevance of the COVID-19 global pandemic, we are releasing our dataset of tweets acquired from the Twitter Stream related to COVID-19 chatter. The first 9 weeks of data (from January 1st, 2020 to March 11th, 2020) contain very low tweet counts as we filtered other data we were collecting for other research purposes, however, one can see the dramatic increase as the awareness for the virus spread. Dedicated data gathering started from March 11th to March 30th&nbsp;which yielded over 4 million tweets a day. We have added additional data provided by our new collaborators from January 27th to February 27th, to provide extra longitudinal coverage.</strong></p>\n\n<p><strong>The data collected from the stream captures all languages, but the higher prevalence are:&nbsp; English, Spanish, and French. We release all tweets and retweets on the full_dataset.tsv file (101,400,452 unique tweets), and a cleaned version with no retweets on the full_dataset-clean.tsv file (20,244,746 unique tweets). There are several practical reasons for us to leave the retweets, tracing important tweets and their dissemination is one of them. For NLP tasks we provide the top 1000 frequent terms in frequent_terms.csv, the top 1000 bigrams in frequent_bigrams.csv, and the top 1000 trigrams in frequent_trigrams.csv. Some general statistics per day are included for both datasets in the statistics-full_dataset.tsv and statistics-full_dataset-clean.tsv files.&nbsp;</strong></p>\n\n<p><strong>More details can be found (and will be updated faster at: <a href=\"https://github.com/thepanacealab/covid19_twitter\">https://github.com/thepanacealab/covid19_twitter</a>)</strong></p>\n\n<p><strong>As always, the tweets distributed here are only tweet identifiers (with date and time added) due to the terms and conditions of Twitter to re-distribute Twitter data. The need to be hydrated to be used. </strong></p>", 
  "license": "", 
  "creator": [
    {
      "affiliation": "Georgia State University", 
      "@id": "https://orcid.org/0000-0001-8499-824X", 
      "@type": "Person", 
      "name": "Banda, Juan M."
    }, 
    {
      "affiliation": "Georgia State University", 
      "@id": "https://orcid.org/0000-0002-1606-4856", 
      "@type": "Person", 
      "name": "Tekumalla, Ramya"
    }, 
    {
      "affiliation": "University of Missouri", 
      "@type": "Person", 
      "name": "Wang, Guanyu"
    }, 
    {
      "affiliation": "Universitat Aut\u00f2noma de Barcelona", 
      "@type": "Person", 
      "name": "Yu, Jingyuan"
    }, 
    {
      "affiliation": "Carl von Ossietzky Universit\u00e4t Oldenburg", 
      "@type": "Person", 
      "name": "Liu, Tuo"
    }, 
    {
      "affiliation": "Universit\u00e4t Duisburg-Essen", 
      "@type": "Person", 
      "name": "Ding, Yuning"
    }, 
    {
      "affiliation": "Georgia State University", 
      "@id": "https://orcid.org/0000-0003-2194-2251", 
      "@type": "Person", 
      "name": "Chowell, Gerardo"
    }
  ], 
  "url": "https://zenodo.org/record/3735274", 
  "datePublished": "2020-03-31", 
  "version": "3.0", 
  "keywords": [
    "social media", 
    "twitter", 
    "nlp", 
    "covid-19", 
    "covid19"
  ], 
  "@context": "https://schema.org/", 
  "distribution": [
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/frequent_bigrams.csv", 
      "encodingFormat": "csv", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/frequent_terms.csv", 
      "encodingFormat": "csv", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/frequent_trigrams.csv", 
      "encodingFormat": "csv", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/full_dataset-clean.tsv.gz", 
      "encodingFormat": "gz", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/full_dataset.tsv.gz", 
      "encodingFormat": "gz", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/statistics-full_dataset-clean.tsv", 
      "encodingFormat": "tsv", 
      "@type": "DataDownload"
    }, 
    {
      "contentUrl": "https://zenodo.org/api/files/323c9677-d77e-41e3-b995-38ac07c9d0ab/statistics-full_dataset.tsv", 
      "encodingFormat": "tsv", 
      "@type": "DataDownload"
    }
  ], 
  "identifier": "https://doi.org/10.5281/zenodo.3735274", 
  "@id": "https://doi.org/10.5281/zenodo.3735274", 
  "@type": "Dataset", 
  "name": "A Twitter Dataset of 100+ million tweets related to COVID-19"
}
98,221
128,849
views
downloads
All versions This version
Views 98,2212,937
Downloads 128,849791
Data volume 186.8 TB170.9 GB
Unique views 76,8232,540
Unique downloads 25,827423

Share

Cite as